Functional Data Research Articles

Impact Assessment and Damage Fee Development for Pavement Utility Cuts Using Functional and Structural Field Data

The objectives of this study were: 1) to provide transparency of a recent pavement utility cut impact study which informed the adoption of a pavement utility cut fee in Davis, California; and 2) to present an additional methodology for assessing pavement damage using field data referenced to pavement condition. A total of 24 test sites were selected to represent all functional classifications across the Pavement Condition Index (PCI) spectrum. Functional and structural field data were collected and analyzed. Of the 24 test sites, 67% exhibited both functional and structural damage with 96% exhibiting at least one form of damage. The average PCI reduction resulting from utility cuts was 5.1 points and the corresponding percent reduction in pavement service life was 6%. Of the test sites, 63% exhibited damage 2 ft from the edge of the patch, thus indicating that the zone of influence extends past the current restoration area. The statistical analyses indicated that the pavement utility cuts caused significant damage and supported a tiered utility cut fee structure based on functional classification and PCI. The resulting fee schedule is based on 2022 material and construction cost estimates; consequently, implementation including an annual adjustment for inflation is recommended. Since the negative impact of utility cuts is amplified when there are multiple or large cuts on the same street, and treatments are typically carried out across entire management sections, a full-recovery fee at a threshold of 10% of the management section area is appropriate. Example fee calculations were provided.

Identifying anomalous patterns in ecological communities’ diversity: leveraging functional boxplots and clustering of normalized Hill’s numbers and their integral functions

AbstractDiversity is fundamental in many disciplines, such as ecology, business, biology, and medicine. From a statistical perspective, calculating a measure of diversity, whatever the context of reference, always poses the same methodological challenges. For example, in the ecological field, although biodiversity is widely recognised as a positive element of an ecosystem, and there are decades of studies in this regard, there is no consensus measure to evaluate it. The problem is that diversity is a complex, multidimensional, and multivariate concept. Limiting to the idea of diversity as variety, recent studies have presented functional data analysis to deal with diversity profiles and their inherently high-dimensional nature. A limitation of this recent research is that the identification of anomalies currently still focuses on univariate measures of biodiversity. This study proposes an original approach to identifying anomalous patterns in environmental communities’ biodiversity by leveraging functional boxplots and functional clustering. The latter approaches are implemented to standardised and normalised Hill’s numbers treating them as functional data and Hill’s numbers integral functions. Each of these functional transformations offers a peculiar and exciting point of view and interpretation. This research is valuable for identifying warning signs that precede pathological situations of biodiversity loss and the presence of possible pollutants.

Variable selection for multivariate functional data via conditional correlation learning

Variable selection for multivariate functional data via conditional correlation learning

Bayesian Inference of Recurrent Switching Linear Dynamical Systems with Higher-Order Dependence

Many complicated dynamical events may be broken down into simpler pieces and efficiently described by a system that shifts among a variety of conditionally dynamical modes. Building on switching linear dynamical systems, we develop a new model that extends the switching linear dynamical systems for better discovering these dynamical modes. In the proposed model, the linear dynamics of latent variables can be described by a higher-order vector autoregressive process, which makes it feasible to evaluate the higher-order dependency relationships in the dynamics. In addition, the transition of switching states is determined by a stick-breaking logistic regression, overcoming the limitation of a restricted geometric state duration and recovering the symmetric dependency between the switching states and the latent variables from asymmetric relationships. Furthermore, logistic regression evidence potentials can appear as conditionally Gaussian potentials by utilizing the Po´lya-gamma augmentation strategy. Filtering and smoothing algorithms and Bayesian inference for parameter learning in the proposed model are presented. The utility and versatility of the proposed model are demonstrated on synthetic data and public functional magnetic resonance imaging data. Our model improves the current methods for learning the switching linear dynamical modes, which will facilitate the identification and assessment of the dynamics of complex systems.

Late-onset Kjellin syndrome: Diagnosis of SPG11 on fundus examination.

Spastic paraplegia (SPG) is a heterogenous group of neurodegenerative disorders, that may include ocular involvement. Here we report the clinical data of a patient with late-onset Kjellin syndrome, a peculiar form of hereditary SPG with macular dystrophy. Clinical, functional and multimodal retinal imaging data were collected. Genetic testing was performed by Whole Exome Sequencing (WES). A 52-year-old female patient with SPG of unknown origin was referred for a progressive visual acuity loss. Multimodal fundus imaging revealed a peculiar macular dystrophy. Given the specific association of macular dystrophy and SPG, a Kjellin syndrome was suspected and genetic testing performed. WES revealed biallelic pathogenic variants in SPG11, co-segregating with disease in the family. Careful ophthalmological examination prompted the diagnosis and guided molecular testing. This case underlines the importance of a neuro-ophthalmologic assessment in patients with SPG.

Wavelet feature screening

An initial screening of which covariates are relevant is a common practice in high-dimensional regression models. The classic feature screening selects only a subset of covariates correlated with the response variable. However, many important features might have a relevant albeit highly nonlinear relation with the response. One screening approach that handles nonlinearity is to compute the correlation between the response and nonparametric functions of each covariate. Wavelets are powerful tools for nonparametric and functional data analysis but are still seldom used in the feature screening literature. We propose a wavelet feature screening method that can be easily implemented, and we prove that, under suitable conditions, it captures the true covariates with high probability. Simulation results also show that our approach outperforms other screening methods in highly nonlinear models. We apply feature screening to two data sets about ozone concentration and epilepsy. In both applications, the proposed method selects features that match findings in the literature of their respective research fields, illustrating the applicability of feature screening. Supplementary material for this article is available online.

Role of interim positron emission tomography/computed tomography in assessment of lymphoma treatment response

BackgroundLymphoma is the most common primary hematological malignancy. FDG PET/CT has recently become the standard imaging modality for clinical management owing to its ability to provide precise, non-invasive anatomical and functional data. The purpose of this study was to highlight the role of 18F FDG-PET/CT in the management of lymphoma by monitoring treatment response, providing a guide for response-adapted therapy, and predicting the final therapeutic outcome.MethodsThis was a prospective monocentric cohort observational study in which thirty-three patients with histopathologically proved lymphoma of different types performed FDG-PET/CT scanning several times throughout the 24-month duration of the study. Early-stage interim SUVmax of the most active lesion (both nodal and/or extra-nodal) was measured and statistically analyzed together with data of the international prognostic index parameters and score.ResultsAmong the included 33 patients of lymphoma, international prognostic index parameters and score together with the early-stage interim SUVmax of the predominant nodal and extra-nodal sites showed statistical significance in predicting the initial as well as the final treatment response after 24 months. Using ROC analysis, we could obtain cutoff values of SUVmax of the predominant nodal lesion of 2.75 (AUC 72%, 95% CI 0.42–1.0) and SUVmax of the predominant extra-nodal lesion of 3 (AUC 70.8% and 95% CI 0.23–1.0); therefore, SUVmax of higher than these values was related to stable or progressive disease, and lower levels than these values were related to complete or partial metabolic response based on Deauville 5-point scale and Lugano response criteria.ConclusionsEarly-stage interim PET-CT SUVmax of the predominant nodal and extra-nodal lesion could be a reliable parameter in predicting initial and final therapeutic outcome in lymphoma patients.

Structural shifts in plant functional diversity during biogeomorphic succession: Moving beyond taxonomic investigations in an alpine glacier foreland

AbstractThe complex interrelation between plants and geomorphic processes is described in the concept of biogeomorphic succession. While ecological research on succession and community assembly has transitioned towards functional approaches, studies on functional diversity in biogeomorphic settings, particularly in glacier forelands, remain limited. In this study, we investigated abundance of vascular plant species and functional traits in an alpine glacier foreland using data from 199 plots. Our objective was to unravel the development of functional diversity during biogeomorphic succession. Specifically, the study determined whether structural shifts in functional diversity are associated with stability thresholds related to plant cover, geomorphic influence, and examined trait spectra for stages of biogeomorphic succession. Our findings revealed a nonlinear trajectory of functional diversity along the plant cover gradient, marked by two distinct structural shifts at 30% and 74% cover, corresponding to established stability thresholds. Along the gradient of geomorphic influence, we observed an increase in functional diversity until 54% of the plot area was affected, beyond which functional diversity declined below the initial level. The analysis of community‐weighted means of traits across four stages of biogeomorphic succession determined by plant cover and absence and presence of geomorphic influence revealed significant differences in trait values. In the transition to the biogeomorphic stage, associated with the identified initial structural shift, there is a shift from a prevalence of above‐ground adaptation and reproductive traits, such as leaf longevity, structure, growth form and mixed reproductive strategies, to an increased dominance of competitor species and traits related to below‐ground structures, including root type and structures, as well as vegetative reproduction. Our results contribute to understanding the relationship between vegetation succession and geomorphic influence by linking them to plant functional traits. This study advances beyond traditional taxonomic investigations by emphasizing functional approaches to biogeomorphic succession. Moreover, the functional trait data used in this study, easily downloadable from a public repository, can serve as a valuable template for future research in (bio)geomorphology, along with the employed methodologies.

A bicoherence approach to analyze multi-dimensional cross-frequency coupling in EEG/MEG data

We introduce a blockwise generalisation of the Antisymmetric Cross-Bicoherence (ACB), a statistical method based on bispectral analysis. The Multi-dimensional ACB (MACB) is an approach that aims at detecting quadratic lagged phase-interactions between vector time series in the frequency domain. Such a coupling can be empirically observed in functional neuroimaging data, e.g., in electro/magnetoencephalographic signals. MACB is invariant under orthogonal trasformations of the data, which makes it independent, e.g., on the choice of the physical coordinate system in the neuro-electromagnetic inverse procedure. In extensive synthetic experiments, we prove that MACB performance is significantly better than that obtained by ACB. Specifically, the shorter the data length, or the higher the dimension of the single data space, the larger the difference between the two methods.

N‐Bu4NI/K2S2O8‐Mediated C–N Coupling between Aldehydes and Amides

n‐Bu4NI/K2S2O8‐mediated C‐N coupling between aldehydes and amides is reported. A strong electronic effect is observed on the aromatic aldehyde substrates. The transformylation from aldehyde to amide takes place exclusively when an aromatic aldehyde bears electron‐donating groups at either the ortho or para position of the formyl group, while the cross‐dehydrogenative coupling dominates in the absence of these groups. Both the density functional theory (DFT) thermochemistry calculations and experimental data support the proposed single electron transfer mechanism with the formation of an acyl radical intermediate in the cross‐dehydrogenative coupling. The n‐Bu4NI/K2S2O8 mediated oxidative cyclization between 2‐aminobenzamide and aldehydes is also reported, with four quinazolin‐4(3H)‐ones prepared in 65‐99% yields.

Allogeneic bone marrow mesenchymal stem cell-derived exosomes alleviate human hypoxic AKI-on-a-Chip within a tight treatment window

BackgroundAcute hypoxic proximal tubule (PT) injury and subsequent maladaptive repair present high mortality and increased risk of acute kidney injury (AKI) - chronic kidney disease (CKD) transition. Human bone marrow mesenchymal stem cell-derived exosomes (hBMMSC-Exos) as potential cell therapeutics can be translated into clinics if drawbacks on safety and efficacy are clarified. Here, we determined the real-time effective dose and treatment window of allogeneic hBMMSC-Exos, evaluated their performance on the structural and functional integrity of 3D microfluidic acute hypoxic PT injury platform.MethodshBMMSC-Exos were isolated and characterized. Real-time impedance-based cell proliferation analysis (RTCA) determined the effective dose and treatment window for acute hypoxic PT injury. A 2-lane 3D gravity-driven microfluidic platform was set to mimic PT in vitro. ZO-1, acetylated α-tubulin immunolabelling, and permeability index assessed structural; cell proliferation by WST-1 measured functional integrity of PT.ResultshBMMSC-Exos induced PT proliferation with ED50 of 172,582 µg/ml at the 26th hour. Hypoxia significantly decreased ZO-1, increased permeability index, and decreased cell proliferation rate on 24–48 h in the microfluidic platform. hBMMSC-Exos reinforced polarity by a 1.72-fold increase in ZO-1, restored permeability by 20/45-fold against 20/155 kDa dextran and increased epithelial proliferation 3-fold compared to control.ConclusionsThe real-time potency assay and 3D gravity-driven microfluidic acute hypoxic PT injury platform precisely demonstrated the therapeutic performance window of allogeneic hBMMSC-Exos on ischemic AKI based on structural and functional cellular data. The novel standardized, non-invasive two-step system validates the cell-based personalized theragnostic tool in a real-time physiological microenvironment prior to safe and efficient clinical usage in nephrology.

The burden and natural history of cardiac pathology at TB diagnosis in a high-HIV prevalence district in Zambia: protocol for the TB-Heart study

BackgroundTuberculosis (TB) continues to be a major cause of death across sub-Saharan Africa (SSA). In parallel, non-communicable disease and especially cardiovascular disease (CVD) burden has increased substantially in the region. Cardiac manifestations of TB are well-recognised but the extent to which they co-exist with pulmonary TB (PTB) has not been systematically evaluated. The aim of this study is to improve understanding of the burden of cardiac pathology in PTB in those living with and without HIV in a high-burden setting.MethodsThis is a cross-sectional and natural history study to evaluate the burden and natural history of cardiac pathology in participants with PTB in Lusaka, Zambia, a high burden setting for TB and HIV. Participants with PTB, with and without HIV will be consecutively recruited alongside age- and sex-matched TB-uninfected comparators on a 2:1 basis. Participants will undergo baseline assessments to collect clinical, socio-demographic, functional, laboratory and TB disease impact data followed by point-of-care and standard echocardiography. Participants with PTB will undergo further repeat clinical and functional examination at two- and six months follow-up. Those with cardiac pathology at baseline will undergo repeat echocardiography at six months.DiscussionThe outcomes of the study are to a) determine the burden of cardiac pathology at TB diagnosis, b) describe its association with patient-defining risk factors and biochemical markers of cardiac injury and stretch and c) describe the natural history of cardiac pathology during the course of TB treatment.

Effects of bilateral tDCS over DLPFC on response inhibition, craving, and brain functional connectivity in Internet gaming disorder: Arandomized, double-blind, sham-controlled trial with fMRI.

Impaired inhibitory control accompanied by enhanced craving is hallmark of addiction. This study investigated the effects of transcranial direct current stimulation (tDCS) on response inhibition and craving in Internet gaming disorder (IGD). We examined the brain changes after tDCS and their correlation with clinical variables. Twenty-four males with IGD were allocated randomly to an active or sham tDCS group, and data from 22 participants were included for analysis. Participants self-administered bilateral tDCS over the dorsolateral prefrontal cortex (DLPFC) for 10 sessions. Stop-signal tasks were conducted to measure response inhibition and participants were asked about their cravings for Internet gaming at baseline and post-tDCS. Functional magnetic resonance imaging data were collected at pre- and post-tDCS, and group differences in resting-state functional connectivity (rsFC) changes from the bilateral DLPFC and nucleus accumbens were examined. We explored the relationship between changes in the rsFC and behavioral variables in the active tDCS group. A significant group-by-time interaction was observed in response inhibition. After tDCS, only the active group showed a decrease in the stop-signal reaction time (SSRT). Although craving decreased, there were no significant group-by-time interactions or group main effects. The anterior cingulate cortex (ACC) showed group differences in post- versus pre-tDCS rsFC from the right DLPFC. The rsFC between the ACC and left middle frontal gyrus was negatively correlated with the SSRT. Our study provides preliminary evidence that bilateral tDCS over the DLPFC improves inhibitory control and could serve as a therapeutic approach for IGD.

Commonality and variance of resting-state networks in common marmoset brains

Animal models of brain function are critical for the study of human diseases and development of effective interventions. Resting-state network (RSN) analysis is a powerful tool for evaluating brain function and performing comparisons across animal species. Several studies have reported RSNs in the common marmoset (Callithrixjacchus; marmoset), a non-human primate. However, it is necessary to identify RSNs and evaluate commonality and inter-individual variance through analyses using a larger amount of data. In this study, we present marmoset RSNs detected using > 100,000 time-course image volumes of resting-state functional magnetic resonance imaging data with careful preprocessing. In addition, we extracted brain regions involved in the composition of these RSNs to understand the differences between humans and marmosets. We detected 16 RSNs in major marmosets, three of which were novel networks that have not been previously reported in marmosets. Since these RSNs possess the potential for use in the functional evaluation of neurodegenerative diseases, the data in this study will significantly contribute to the understanding of the functional effects of neurodegenerative diseases.

Identification of abnormal closed-loop pathways in patients with MRI-negative pharmacoresistant epilepsy.

Epilepsy is a disorder of brain networks, that is usually combined with cognitive and emotional impairment. However, most of the current research on closed-loop pathways in epilepsy is limited to the neuronal level or has focused only on known closed-loop pathways, and studies on abnormalities in closed-loop pathways in epilepsy at the whole-brain network level are lacking. A total of 26 patients with magnetic resonance imaging-negative pharmacoresistant epilepsy (MRIneg-PRE) and 26 healthy controls (HCs) were included in this study. Causal brain networks and temporal-lag brain networks were constructed from resting-state functional MRI data, and the Johnson algorithm was used to identify stable closed-loop pathways. Abnormal closed-loop pathways in the MRIneg-PRE cohort compared with the HC group were identified, and the associations of these pathways with indicators of cognitive and emotional impairments were examined via Pearson correlation analysis. The results revealed that the abnormal stable closed-loop pathways were distributed across the frontal, parietal, and occipital lobes and included altered functional connectivity values both within and between cerebral hemispheres. Four abnormal closed-loop pathways in the occipital lobe were associated with emotional and cognitive impairments. These abnormal pathways may serve as biomarkers for the diagnosis and guidance of individualized treatments for MRIneg-PRE patients.

Functional magnetic resonance imaging of the brain in patients with insomnia: a prospective study

INTRODUCTION: Insomnia is one of the most common sleep disorders, the interest of scientists in the occurrence and pathophysiology of insomnia is growing every year. In particular, the brain connectome and its changes in sleep disorders are being actively studied based on the data of resting state functional magnetic resonance imaging.OBJECTIVE: The study is to assess changes in brain connectomes in patients with chronic insomnia using functional magnetic resonance imaging.MATERIALS AND METHODS: 53 people took part in the study, of which 34 patients who applied for a somnologist’s appointment at the Almazov National Research Medical Center of the Ministry of Health of the Russian Federation were diagnosed with chronic insomnia, confirmed by polysomnography. All participants of the study had an MRI of the brain on tomographs with a magnetic field induction force of 3.0 Tl at two time points.Statistics: Statistical analysis of MRI data was performed using MathLab 2018a, CONN v1.7. Descriptive statistics, the Kolmogorov-Smirnov criterion were used to process the materials, depending on the characteristics of the data, the MannWhitney U-criterion and Pearson Chi-squared were used to analyze demographic data.RESULTS: The study, neuroimaging markers of insomnia were identified and changes in the functional networks of the brain were described in patients with insomnia and a group of healthy volunteers at different time points.DISCUSSION: The obtained functional data demonstrate ambiguous results. Both an increase and a decrease in the functional connectivity of the medial prefrontal cortex with the structures of the visual analyzer, an increase in functional connections with the temporal pole, in particular with the hippocampus, is determined, which indicates changes in the consolidation of visually encoded information. The relative limitation in this study can be considered the heterogeneity of the age composition of the group.CONCLUSSION: Resting state functional MRI of the brain is a key neuroimaging method in determining the functional connections of the brain in patients with sleep disorders, which allows us to establish a impairment of functional interaction between brain structures involved in the processes of falling asleep and maintaining sleep.

Two level neuro-functional forecaster: A novel dynamic hybridization for functional data forecasting

With the advancement of technology, time series data are automatically collected without human intervention. As the data collection process becomes effortless, the next change encountered is to identify the best method to forecast time series data with high accuracies. In this regard, hybrid approaches have gained much attention where the strengths of two approaches can be combined to lessen the weaknesses of each individual approach. When exploring the features of time series data, some depict repetitive patterns and also data can be observed at several levels. The repeating curves can be considered as the higher level, whereas each individual observation can be considered as the lower level. Thus, in order to handle the data in a more effective way, the series can be handled at two levels by giving prominence to the features of each level separately. This paper proposes a novel algorithm named two level neuro-functional forecaster, which is capable of handling data at two levels, hybridizing a statistical approach with an artificial intelligence approach, to gain high accuracy levels. In addition, as this approach handles data at two levels, data sparsity at a particular level can be accommodated at the other level. To apply this algorithm to a real world dataset, electricity demand data in Sri Lanka was considered where the series consisted of daily load curves with repetitive pattern across the days. The proposed hybrid algorithm, outperforms the two approaches when individually used, with a MAPE of 3.324% for a year.

Two cases of gastric cancer with elevated serum levels of KL-6

BackgroundThe serum level of Krebs von den Lungen-6 (sKL-6) is a biomarker of interstitial pneumonia and has been reported to be elevated in patients with cancers. However, there have been few cases of gastric cancer (GC) with elevated sKL-6 that were treated by chemotherapy. We herein report two cases of GC with elevated sKL-6 that were treated with oxaliplatin plus S-1 (SOX) chemotherapy and discussed the resulting changes in sKL-6.Case presentationThe first patient was a 79-year-old woman complaining of loss of appetite. Esophagogastroduodenoscopy (EGD) showed a type-3 tumor in the gastric antrum and biopsy specimens showed adenocarcinoma. Computed tomography (CT) showed multiple liver metastases. sKL-6 was elevated to 1,292 U/ml, but a CT revealed no obvious lesions of the lungs, including interstitial pneumonia. The tumor was diagnosed as GC with liver metastases and elevated sKL-6. Respiratory function data were normal. SOX therapy using oxaliplatin and S-1 was performed. After 3 courses of SOX therapy, CT showed reductions of the liver metastases as well as the primary tumor, and sKL-6 was decreased to 201 U/ml. After the 44 courses, sKL-6 was slightly elevated. Chest CT showed interstitial pneumonia and chemotherapy was stopped. The patient is still alive without any metastasis 72 months later. The second patient was a 69-year-old woman complaining of upper abdominal pain. EGD revealed a type-3 tumor in the gastric antrum showing adenocarcinoma with HER2-positive pathology. CT showed multiple node metastases around the abdominal aorta. sKL-6 was elevated to 2,239 U/ml, but a respiratory function test showed no abnormalities, and CT of the lungs showed no obvious lesions. The tumor was diagnosed as GC with distant node metastases and elevated sKL-6. The patient received SOX therapy combined with trastuzumab. After 6 courses, the size of the primary tumor and multiple node metastases were reduced, and sKL-6 was decreased to 284 U/ml.ConclusionsThese two cases suggest that sKL-6 may be important not only as an indicator of interstitial pneumonia in chemotherapeutic courses, but also as a tumor marker in GC patients with multiple metastases.

Response accuracy of ChatGPT 3.5 Copilot and Gemini in interpreting biochemical laboratory data a pilot study.

With the release of ChatGPT at the end of 2022, a new era of thinking and technology use has begun. Artificial intelligence models (AIs) like Gemini (Bard), Copilot (Bing), and ChatGPT-3.5 have the potential to impact every aspect of our lives, including laboratory data interpretation. To assess the accuracy of ChatGPT-3.5, Copilot, and Gemini responses in evaluating biochemical data. Ten simulated patients' biochemical laboratory data, including serum urea, creatinine, glucose, cholesterol, triglycerides, low-density lipoprotein (LDL-c), and high-density lipoprotein (HDL-c), in addition to HbA1c, were interpreted by three AIs: Copilot, Gemini, and ChatGPT-3.5, followed by evaluation with three raters. The study was carried out using two approaches. The first encompassed all biochemical data. The second contained only kidney function data. The first approach indicated Copilot to have the highest level of accuracy, followed by Gemini and ChatGPT-3.5. Friedman and Dunn's post-hoc test revealed that Copilot had the highest mean rank; the pairwise comparisons revealed significant differences for Copilot vs. ChatGPT-3.5 (P = 0.002) and Gemini (P = 0.008). The second approach exhibited Copilot to have the highest accuracy of performance. The Friedman test with Dunn's post-hoc analysis showed Copilot to have the highest mean rank. The Wilcoxon Signed-Rank Test demonstrated an indistinguishable response (P = 0.5) of Copilot when all laboratory data were applied vs. the application of only kidney function data. Copilot is more accurate in interpreting biochemical data than Gemini and ChatGPT-3.5. Its consistent responses across different data subsets highlight its reliability in this context.

Full endoscopic laminotomy decompression versus anterior cervical discectomy and fusion for the treatment of single-segment cervical spinal stenosis: a retrospective, propensity score-matched study.

Anterior cervical discectomy and fusion (ACDF) is the standard procedure for the treatment of cervical spinal stenosis (CSS), but complications such as adjacent segment degeneration can seriously affect the long-term efficacy. Currently, posterior endoscopic surgery has been increasingly used in the clinical treatment of CSS. The aim of this study was to compare the clinical outcomes of single-segment CSS patients who underwent full endoscopic laminotomy decompression or ACDF. 138 CSS patients who met the inclusion criteria from June 2018 to August 2020 were retrospectively analyzed and divided into endoscopic and ACDF groups. The propensity score matching (PSM) method was used to adjust the imbalanced confounding variables between the groups. Then, perioperative data were recorded and clinical outcomes were compared, including functional scores and imaging data. Functional scores included Visual Analog Scale of Arms (A-VAS) and Neck pain (N-VAS), Japanese Orthopedic Association score (JOA), Neck Disability Index (NDI), and imaging data included Disc Height Index (DHI), Cervical range of motion (ROM), and Ratio of grey scale (RVG). After PSM, 84 patients were included in the study and followed for 24-30months. The endoscopic group was significantly superior to the ACDF group in terms of operative time, intraoperative blood loss, incision length, and hospital stay (P < 0.001). Postoperative N-VAS, A-VAS, JOA, and NDI were significantly improved in both groups compared with the preoperative period (P < 0.001), and the endoscopic group showed better improvement at 7days postoperatively (P < 0.05). The ROM changes of adjacent segments were significantly larger in the ACDF group at 12months postoperatively and at the last follow-up (P < 0.05). The RVG of adjacent segments showed a decreasing trend, and the decrease was more marked in the ACDF group at last follow-up (P < 0.05). According to the modified MacNab criteria, the excellent and good rates in the endoscopic group and ACDF group were 90.48% and 88.10%, respectively, with no statistically significant difference (P > 0.05). Full endoscopic laminotomy decompression is demonstrated to be an efficacious alternative technique to traditional ACDF for the treatment of single-segment CSS, with the advantages of less trauma, faster recovery, and less impact on cervical spine kinematics and adjacent segmental degeneration.